10967/264 - QDB Compounds

QsarDB Repository

Belfield, S. J.; Cronin, M. T. D.; Enoch, S. J.; Firman, J. W. Guidance for Good Practice in the Application of Machine Learning in Development of Toxicological Quantitative Structure-Activity Relationships (QSARs). PLOS ONE, 2023, 18, e0282924.

Compound

ID:1949
Name:1-(4-phenylphenyl)ethan-1-one
Description:
Labels:Neutral
CAS:92-91-1
InChi Code:InChI=1/C14H12O/c1-11(15)12-7-9-14(10-8-12)13-5-3-2-4-6-13/h2-10H,1H3

Properties

pIGC50: 40-h Tetrahymena toxicity as log(1/IGC50) [log(L/mmol)] i

ValueSource or prediction
0.92

experimental value

1.07

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)

1.38

RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)

0.93

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)

1.21

SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)

1.15

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)

1.15

KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)

1.0

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)

1.37

XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)

1.01

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)

1.3

SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)

0.97

DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)

1.24

DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)